So sánh phương pháp

	Dự báo Chuỗi Thời gian bằng Dự đoán Hợp thức	Hồi quy Quantile
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	2021	1978
Người khởi xướng	Angelopoulos & Bates (tutorial); Xu & Xie (time-series EnbPI)	Koenker & Bassett
Loại	Distribution-free prediction interval wrapper	Conditional quantile regression
Công trình gốc	Angelopoulos, A. N. & Bates, S. (2023). Conformal Prediction: A Gentle Introduction. Foundations and Trends in Machine Learning, 16(4), 494-591.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Tên gọi khác	conformal prediction, distribution-free prediction intervals, EnbPI, Konformal Tahmin (Conformal Prediction — Zaman Serisi)	conditional quantile regression, regression quantiles, Kantil Regresyon
Liên quan	4	5
Tóm tắt	Conformal prediction is a distribution-free wrapper that turns any point forecaster — ARIMA, a neural network, or a machine-learning model — into valid prediction intervals using only its residuals. The time-series form was popularised by Xu & Xie (2021) and the modern tutorial treatment by Angelopoulos & Bates (2023).	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.